Data Collaborative

Description

Stefaan Verhulst and David Sangokoya:

"Much of the data valuable for solving public problems actually resides within the private sector — for example, in the form of click histories, online purchases, sensor data, and, as in the case of the above example, call data records. Amid the proliferation of apps, platforms and sensors, data on how people and societies behave is increasingly privately owned. We believe that if we truly want to leverage the potential of data to improve people’s lives, then we need to accelerate the creation and use of “data collaboratives.”

The term data collaborative refers to a new form of collaboration, beyond the public-private partnership model, in which participants from different sectors — including private companies, research institutions, and government agencies — can exchange data to help solve public problems. In the coming months and years, data collaboratives will be essential vehicles for harnessing the vast stores of privately held data toward the public good.

Benefits

Stefaan Verhulst and David Sangokoya:

"At the GovLab, we have identified the following benefits — all contributing to the broader potential of improving people’s lives:

Data-driven decision-making: In an information age, data from a wide variety of sources (private and public) is critical in enabling policymakers and other decision-makers to address major societal challenges. For example, Californian urban planners make decisions regarding the distribution of water resources by relying on models that help determine water availability and use data to adjust agricultural and commercial practices accordingly. Their decisions are guided by data and analytics tools from numerous sources, including Intel, the Earth Research Institute at the University of California at Santa Barbara, and the World Food Center at the University of California at Davis. Ultimately, it is the collaboration of expertise and data from these various sources that will help determine the success of the state’s water use strategies.

Information exchange and coordination: Data collaboratives also add value by creating important platforms for information exchange and coordination among data providers and users. A good example can be found in the realm of clinical drug trials. Until recently, a substantial amount of the existing scientific data resulting from drug trials remained in private companies’ hands, inaccessible to independent researchers and citizen groups who could have added insights about drug safety and effectiveness. But in recent years, a number of leading pharmaceutical and medical device companies — including GSK, Lilly, and Novartis — have started making their clinical study results available to outside researchers via a central website (clinialstudydatarequest.com). Since January 2014, over 10 pharmaceutical companies have provided more than 1200 listed studies.

Shared standards and frameworks to enable multi-actor, multi-sector participation: Data collaboratives can also increases synergies within the data community (data collectors, data integrators, data policy experts and data scientists), facilitating the emergence of much-needed standards and frameworks to make data interoperable and useful across organizations and sectors. With data emerging from an increasing variety of sources, and being used by a growing diversity of actors, such shared standards are essential to unleashing the full potential of data."

Examples

Stefaan Verhulst and David Sangokoya:

"Examples include the following:

"In January 2015, the Obama Administration unveiled the Precision Medicine Initiative, a new model of patient-powered research and engagement that aims to build a knowledge base for individualized medicine. Specifically, the Initiative builds partnerships that enable it to include data from a number of existing research cohorts, patient groups, and private-sector labs to expand our understanding of cancer genomics and eventually allow for treatments tailored to individual patients’ genetic profiles.

The Mobile Data, Environmental Extremes and Population (MDEEP) Project is a collaborative partnership between the United Nations University Institute for Environment and Human Security (UNU-EHS), the International Centre for Climate Change and Development (ICCCAD), Flowminder.org, Telenor Group and Grameenphone. Grameenphone, the leading telecommunications provider in Bangladesh, shares its mobile call data records to allow greater understanding of climate impacts by mapping population flows before and after extreme weather events.

Founded in 2014 with a grant from Twitter, MIT’s Laboratory for Social Machines seeks to analyze networked, social data to measure and improve learning outcomes, help governments better assess citizen needs, and improve our understanding of how information travels in the public sphere. Crucially, Twitter’s contribution consisted not only of $10 million in direct funding, but also the granting of full access (via Twitter-acquired social media aggregator GNIP) to its complete corpus of public tweets."